Education
2013 - 2018
Bachelor of Engineering in Electrical Engineering with double minors in Mathematics and Computer-Science
Montreal, Canada
During my time at McGill University, I developed a strong foundation in engineering. I managed to complete a wide number of courses encompassing: Circuit Design, Digital System Design, Telecommunication networks, Power and Computer Engineering.
My passion for logic and truth also pushed me at that time to complete a double minor in Math and CS, enabling me to expand my skillset in the fields of programming, artificial intelligence, machine learning, as well as mathematical analysis and complex systems.
2016
Adelaide, Australia
At University of Adelaide, I pursued my passion for music, mathematics and engineering. During my exchange semester over there, I successfully completed courses in Sounds Engineering, Control Systems and Algebra .
2022
Data Science Retreat
Berlin, Germany
Completed projects in relation with Data Science and engineering. Applied Supervised and Unsupervised learning algorithms such as regression, classification, time-series analysis, clustering and PCA. Participated and won first place in the organized kaggle competition for sales prediction. Additionally worked with NLP and computer-vision techniques to deal with unstructured data. Finally completed a proof-of-concept project for Reinforcement Learning in the field of telecommunication networks.
Online Certificates
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Deep Learning Specialization
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Convolutional Neural Networks
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Sequence Models
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Improving Deep Neural Networks
Books
"Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play" - David Foster
"Reinforcement Learning" - Richard S. Sutton and Andrew G.Barto
"Graph Representation Learning" - William L. Hamilton
Programming Languages
Python
Java
Matlab
C
SQL
HTML/CSS
R